The PROSPER-HIV Study: A Research Protocol to Examine Relationships Among Physical Activity, Diet Intake, and Symptoms in Adults Living With HIV.
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ABSTRACT:
SUBMITTER: Webel AR
PROVIDER: S-EPMC7313388 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PURPOSE:Physical inactivity is associated with disruptions in glucose metabolism and energy balance, whereas energy restriction may blunt these adverse manifestations. During hypocaloric feeding, higher-protein intake maintains lean mass which is an important component of metabolic health. This study determined whether mild energy restriction preserves glycemic control during physical inactivity and whether this preservation is more effectively achieved with a higher-protein diet. METHODS:Ten adults (24 ± 1 yr) consumed a control (64% carbohydrate, 20% fat, 16% protein) and higher-protein diet (50% carbohydrate, 20% fat, 30% protein) during two 10-d inactivity periods (>10,000 → ~5000 steps per day) in a randomized crossover design. Energy intake was decreased by ~400 kcal·d to account for reduced energy expenditure associated with inactivity. A subset of subjects (n = 5) completed 10 d of inactivity while consuming 35% excess of their basal energy requirements, which served as a positive control condition (overfeeding+inactivity). RESULTS:Daily steps were decreased from 12,154 ± 308 to 4275 ± 269 steps per day (P < 0.05) which was accompanied by reduced V˙O2max (-1.8 ± 0.7 mL·kg·min, P < 0.05), independent of diet conditions. No disruptions in fasting or postprandial glucose, insulin, and nonesterified fatty acids in response to 75 g of oral glucose were observed after inactivity for both diet conditions (P > 0.05). Overfeeding+inactivity increased body weight, body fat, homeostasis model assessment of insulin resistance, and 2-h postprandial glucose and insulin concentrations (P < 0.05), despite no changes in lipid concentrations. CONCLUSIONS:We show that independent of diet (normal vs higher-protein), mild energy restriction preserves metabolic function during short-term inactivity in healthy subjects. That is, metabolic deterioration with inactivity only manifests in the setting of energy surplus.
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Project description:Objective: Shift work is associated with risk for adverse health outcomes including cardiovascular disease, type 2 diabetes, cancer, and obesity. Short sleep duration combined with disruptions to the circadian system may alter factors involved with the behavioral regulation of energy intake and expenditure. We aimed to determine how shift work affects sleep, food intake, and physical activity.Methods: This was a field-based observational study using objective assessments of sleep and physical activity and a 24-hour dietary recall in shift workers. Day (n = 12) and night (n = 12) hospital shift workers (nurses and technicians) who were women had their free-living sleep and physical activity tracked via accelerometry, and completed a computer-assisted 24-hour food recall, during a series of work shifts.Results: Compared to day workers, night workers had significantly shorter sleep duration and reported more premature awakenings and feeling less refreshed upon awakening. Daily self-reported energy and macronutrient intakes were not different between groups, although the night shift workers reported a significantly longer total daily eating duration window than day workers. Objectively recorded physical activity levels were not different between groups.Conclusions: The present findings confirm that sleep is disturbed in women night workers, while there are relatively less effects on objectively recorded physical activity and self-reported food intake. We also observed a prolonged daily eating duration in night vs. day workers. These observations can help inform the design of novel behavioral interventions, including, potentially, time restricted feeding approaches (e.g., by limiting daily eating episodes to within a 10-12 h window), to optimize weight management in shift workers.
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Project description:BACKGROUND:Electronic health (eHealth) and mobile health (mHealth) approaches to address low physical activity levels, sedentary behavior, and unhealthy diets have received significant research attention. However, attempts to systematically map the entirety of the research field are lacking. This gap can be filled with a bibliometric study, where publication-specific data such as citations, journals, authors, and keywords are used to provide a systematic overview of a specific field. Such analyses will help researchers better position their work. OBJECTIVE:The objective of this review was to use bibliometric data to provide an overview of the eHealth and mHealth research field related to physical activity, sedentary behavior, and diet. METHODS:The Web of Science (WoS) Core Collection was searched to retrieve all existing and highly cited (as defined by WoS) physical activity, sedentary behavior, and diet related eHealth and mHealth research papers published in English between January 1, 2000 and December 31, 2016. Retrieved titles were screened for eligibility, using the abstract and full-text where needed. We described publication trends over time, which included journals, authors, and countries of eligible papers, as well as their keywords and subject categories. Citations of eligible papers were compared with those expected based on published data. Additionally, we described highly-cited papers of the field (ie, top ranked 1%). RESULTS:The search identified 4805 hits, of which 1712 (including 42 highly-cited papers) were included in the analyses. Publication output increased on an average of 26% per year since 2000, with 49.00% (839/1712) of papers being published between 2014 and 2016. Overall and throughout the years, eHealth and mHealth papers related to physical activity, sedentary behavior, and diet received more citations than expected compared with papers in the same WoS subject categories. The Journal of Medical Internet Research published most papers in the field (9.58%, 164/1712). Most papers originated from high-income countries (96.90%, 1659/1717), in particular the United States (48.83%, 836/1712). Most papers were trials and studied physical activity. Beginning in 2013, research on Generation 2 technologies (eg, smartphones, wearables) sharply increased, while research on Generation 1 (eg, text messages) technologies increased at a reduced pace. Reviews accounted for 20 of the 42 highly-cited papers (n=19 systematic reviews). Social media, smartphone apps, and wearable activity trackers used to encourage physical activity, less sedentary behavior, and/or healthy eating were the focus of 14 highly-cited papers. CONCLUSIONS:This study highlighted the rapid growth of the eHealth and mHealth physical activity, sedentary behavior, and diet research field, emphasized the sizeable contribution of research from high-income countries, and pointed to the increased research interest in Generation 2 technologies. It is expected that the field will grow and diversify further and that reviews and research on most recent technologies will continue to strongly impact the field.
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Project description:ObjectivesWe examined differences in depressive symptoms among people 65 and older who live alone, exploring whether these differences are associated with both health and environmental contexts.MethodData are from the 2006 wave of Health Retirement Study (N = 2,956, age range: 65-104). We used a two-step cluster analytical approach to identify subgroups of health-limitation profiles and environmental profiles. Logistic regression models determined associations between subgroups and depressive symptoms.ResultsCluster analysis identified four health-profile subgroups (sensory-cognitively impaired, physically impaired, multiply impaired, and healthy) and three different physical-social environmental-profile subgroups (physically average/socially unsupported, physically unsupported/socially supported, and physically supported/socially above average). Compared to members of healthier groups, members of the multiply impaired group were the oldest and were more likely both to live in senior housing and to have depressive symptoms if they lived in a physically average/socially unsupported environment. Members of the sensory-cognitively impaired group were more likely to have depressive symptoms when they lived in a physically unsupported/socially supported environment.DiscussionFindings regarding the range of both health and social-physical environmental profiles as well as the associations between person-environment profiles combinations (fit) and depressive symptomatology have important policy and intervention implications.
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